Neurological profiles for market matching and stimulus presentation

ABSTRACT

A neurological profile associated with introversion/extroversion levels, simultaneous visual element processing capability, and/or dynamism processing capability, etc., is determined to select market categories and stimulus material targeted to the particular neurological profile. The neurological profile is determined using information such as user input, user activity, social and environmental factors, genetic and developmental factors, and/or neuro-response data. The neurological profile can be matched with corresponding neurological profile templates to select market categories and stimulus material.

RELATED APPLICATION

This patent arises from a continuation of U.S. patent application Ser.No. 12/410,380, filed on Mar. 24, 2009, entitled “Neurological Profilesfor Market Matching and Stimulus Presentation.” U.S. patent applicationSer. No. 12/410,380 is hereby incorporated by reference in its entity.Priority to U.S. patent application Ser. No. 12/410,380 is herebyclaimed.

TECHNICAL FIELD

The present disclosure relates to neurological profiles. Moreparticularly, the present disclosure relates to determining neurologicalprofiles for market matching and stimulus presentation.

DESCRIPTION OF RELATED ART

A variety of conventional systems are available for presentingadvertising to a user. In some instances, advertising can bepersonalized based on demographic information. For example, a web sitemay identify a user's gender and present product matches directed tothat gender. A program having a predominantly wealthier audience mayinclude advertising directed at wealthier individuals. Viewers in aparticular local market may be presented with commercials tailored tothat local market.

Although a variety of advertising presentation mechanisms are available,the ability to tailor results to a particular user or group are limited.Consequently, it is desirable to provide improved mechanisms forperforming market matching and stimulus presentation.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may best be understood by reference to the followingdescription taken in conjunction with the accompanying drawings, whichillustrate particular example embodiments.

FIG. 1 illustrates one example of a system for performing marketmatching and stimulus presentation.

FIG. 2 illustrates one example of a neurological profile associated withdetermining introversion/extroversion.

FIG. 3 illustrates one example of a neurological profile associated withdetermining visual element limitations.

FIG. 4 illustrates one example of neuro-response data associated withevaluating simultaneous visual element processing.

FIG. 5 illustrates one example of a system for analyzing a categoricalperception shift boundary and implementing neurologically informedmorphing.

FIG. 6 illustrates one example of a technique for performing marketmatching and stimulus presentation using a neurological profile.

FIG. 7 provides one example of a system that can be used to implementone or more mechanisms.

DESCRIPTION OF PARTICULAR EMBODIMENTS

Reference will now be made in detail to some specific examples of theinvention including the best modes contemplated by the inventors forcarrying out the invention. Examples of these specific embodiments areillustrated in the accompanying drawings. While the invention isdescribed in conjunction with these specific embodiments, it will beunderstood that it is not intended to limit the invention to thedescribed embodiments. On the contrary, it is intended to coveralternatives, modifications, and equivalents as may be included withinthe spirit and scope of the invention as defined by the appended claims.

For example, the techniques and mechanisms of the present invention willbe described in the context of particular types of media. However, itshould be noted that the techniques and mechanisms of the presentinvention apply to a variety of different types of media. In thefollowing description, numerous specific details are set forth in orderto provide a thorough understanding of the present invention. Particularexample embodiments of the present invention may be implemented withoutsome or all of these specific details. In other instances, well knownprocess operations have not been described in detail in order not tounnecessarily obscure the present invention.

Various techniques and mechanisms of the present invention willsometimes be described in singular form for clarity. However, it shouldbe noted that some embodiments include multiple iterations of atechnique or multiple instantiations of a mechanism unless notedotherwise. For example, a system uses a processor in a variety ofcontexts. However, it will be appreciated that a system can use multipleprocessors while remaining within the scope of the present inventionunless otherwise noted. Furthermore, the techniques and mechanisms ofthe present invention will sometimes describe a connection between twoentities. It should be noted that a connection between two entities doesnot necessarily mean a direct, unimpeded connection, as a variety ofother entities may reside between the two entities. For example, aprocessor may be connected to memory, but it will be appreciated that avariety of bridges and controllers may reside between the processor andmemory. Consequently, a connection does not necessarily mean a direct,unimpeded connection unless otherwise noted.

Overview

A neurological profile associated with introversion/extroversion levels,simultaneous visual element processing capability, and/or dynamismprocessing capability, etc., is determined to select market categoriesand stimulus material targeted to the particular neurological profile.The neurological profile is determined using information such as userinput, user activity, social and environmental factors, genetic anddevelopmental factors, and/or neuro-response data. The neurologicalprofile can be matched with corresponding neurological profile templatesto select market categories and stimulus material.

Example Embodiments

A variety of mechanisms for matching particular demographiccharacteristics associated with a user with particular products,services, and people are available. In one example, a web siterecognizes that an individual lives in a particular city and providesservices messages associated with that city. In another example, aretailer knows a buyer's purchasing patterns and sends marketingmaterials tailored to those purchasing patterns. In still anotherexample, a networking site determines a user's interests and makesmatches based on those interests.

Providing market matching and stimulus presentation services based ondemographic characteristics is effective but limited. Somecharacteristics associated with a user or buyer may not be easilydiscernible. In many instances, subjects may not even be aware of theirown preferences, capabilities, and behaviors. The techniques andmechanisms of the present invention recognize that cognitive, social,and emotional behavior is influenced by social, environmental, andgenetic factors reflected in neurological profiles.

According to various embodiments, neurological profiles associated withusers are determined to better perform market matching and stimuluspresentation. In particular embodiments, introversion/extroversionlevels associated with a user are determined in order to tailoradvertising to the user. For example, an extroverted user is presentedwith an image showing a large group of people while an introverted useris presented with an image showing one or two people. Advertisingtailored to particular introversion/extroversion levels may be selectedand tailored to the user. The techniques and mechanisms of the presentinvention recognize that introverted users may be uncomfortable whenprovided with materials showing large groups. Introversion/extroversionlevels may be provided by a user, determined based on user activity,ascertained using social, environmental, and/or genetic factors, ordetermined using neuro-response data.

According to various embodiments, neurological profiles are generatedfor users and the neurological profiles are matched with cognitive,social, demographic, and behavioral measures of marketing response. Inparticular embodiments, extroverted individuals may respond positivelyto party invitations while introverted individuals may respondpositively to book signings. Marketing categories or stimulus materialscan be associated with particular neurological profiles or templates.

In another example, the number of visual elements a user cansimultaneously process is determined. According to various embodiments,it is recognized that some individuals can simultaneously process threevisual elements while others can process five visual elements. Inparticular embodiments, the three visual elements may be three portionsof a webpage. The number of visual elements simultaneously processed candecrease with age. According to various embodiments, the number ofsimultaneous visual elements can be automatically selected based ondemographic information, user selection, social, environmental, and/orgenetic factors, and/or neuro-response data.

According to various embodiments, neurological profiles will showincreased neuro-response activity up to the maximum number of visualelements a user can process. Advertising, websites, and other stimuluscan be tailored to particular individuals based on visual elementprocessing capabilities.

In still other examples, the amount of detail a user is drawn do isdetermined using neurological profiles. According to variousembodiments, it is recognized that particular populations, groups, andsubgroups of people are drawn to detail while others generally disregarddetail. The amount of detail includes intricacies in the design of aproduct. According to various embodiments, marketing categoriespresented to a user can be automatically selected based on demographicinformation, user selection, social, environmental, and/or geneticfactors, and/or neuro-response data.

Although particular neurological profile characteristics are described,it should be noted that a wide variety of characteristics may beevaluated using neurological profiles. According to various embodiments,the amount of dynamism needed in media to elicit a response may bedetermined using neurological profiles. In particular embodiments,younger individuals growing up in a more media immersed environment mayrequire more constantly dynamism and changing visual elements in orderto hold attention. The number of distracters, number of repetitions, orthe length of a message may also be varied based on neurologicalprofiles.

The targeted premium placements and advertisement spots can be presentedto a user on social networking sites, job placements sites, programcommercials, or other media.

FIG. 1 illustrates one example of a system for generating neurologicalprofiles for market matching and stimulus presentation. According tovarious embodiments, a neurological profile generator 111 receives userinformation. In particular embodiments, the user information includesuser input data 101, user activity 103, social, genetic, andenvironmental factors 105, and neuro-response data 107. The user inputdata 101 may be forms or surveys completed by a user. User activity 103may include user media consumption patterns and purchasing patterns. Forexample, user activity 103 may indicate that a user prefers highlyadorned and detail oriented web content. Social, genetic, andenvironmental factors 105 may include profiles of friends and familymembers, cultural and genetic differences, etc.

According to various embodiments, users in a particular country may morelikely be introverted than users in other countries. In another example,an individual subscribing to a particular religion may more likelyprefer certain types of activities. In particular embodiments,neuro-response data 107 may also be obtained. Neuro-response data 107may be obtained from the user individually or deduced from other data.Neuro-response data 107 may include user responses collected usingElectroencephalography (EEG) or function Magnetic Resonance Imaging(fMRI) when exposed to particular stimulus material such as videoshowing large groups of people or highly ornate print advertisements.

In particular embodiments, the neurological profile generator 111receives and user information and generate neurological profiles ofusers, user subgroups, and user groups. According to variousembodiments, the neurological profiles identifyintroversion/extroversion levels 121, simultaneous visual elementprocessing capability 123, detail processing levels 125, etc. Theneurological profile generator 111 may determine that a particular useris introverted, can processing 3 visual elements simultaneously, anddoes not have an eye for detail. Although on particular types ofneurological profile information are described, it should be noted thatother neurological profile characteristics can also be determined. Forexample, levels of optimism/pessimism, thinking/feeling,judging/perceiving, and sensing/intuition can be identified using aneurological profile generator 111. The neurological profile informationis passed to a stimulus selection device 131.

According to various embodiments, the stimulus selection device 131matches neurological profile information to cognitive, social,demographic, and behavioral measures of marketing response. Marketingcategories and materials can be matched to particular neurologicalprofiles. In particular embodiments, a template database 133 is accessedto perform matching. The stimulus selection device may indicate thatcertain types or versions of advertisements are more appropriate for auser with a particular neurological profile.

According to various embodiments, the market matching stimulus selectiondevice 131 provides selection information to entities such asservice/content providers 143, media databases 141, and media devices145. Programming, social network sites, shopping destinations, can placetargeted premium placements and advertisement spots 151 as well asprovide targeted products and services.

FIG. 2 illustrates one example of obtaining a neurological profileassociated with introversion/extroversion. According to variousembodiments, user input is received at 201. User input may include usersubmitted forms, surveys, and evaluations. At 205, user activity isanalyzed. User activity may include purchasing patterns, activitypatterns, etc. Although user input and user activity is described, itshould be noted that in various embodiments, user input and useractivity may not be used or available. According to various embodiments,social, cultural, and genetic factors are analyzed at 207. Social,cultural, and genetic factors can have significant correlations withuser extroversion and introversion levels. In particular embodiments,subjects growing up exposed to a particular culture may tend to be muchmore introverted than subjects growing up exposed to another culture. Itshould be noted that other factors such as developmental or neo-natalfactors can be evaluated as well.

According to various embodiments, subjects are exposed to extrovertoriented and introvert oriented stimulus at 209. Extrovert orientedstimulus may include video scenes of a large group gathering or socialevent. Introvert oriented stimulus may include video scenes of readingor relaxing alone. Subjects may also be exposed to stimulus material ingroup and individual settings at 211 to further gaugeintroversion/extroversion levels. At 213, neuro-response data is receiveand analyzed to determine subject neuro-response activity when exposedto extrovert oriented stimulus and introvert oriented stimulus in groupand individual settings. Responses may be compared to responses of knownintroverts and extroverts and/or analyzed to determine attention,emotional engagement, and memory retention levels in response to thestimulus.

FIG. 3 illustrates one example of determining a neurological profileassociated with simultaneous visual element processing capabilities.According to various embodiments, user input is received at 301. Userinput may include user submitted forms, surveys, and evaluations. At305, user activity is analyzed. User activity may include purchasingpatterns, activity patterns, etc. Although user input and user activityis described, it should be noted that in various embodiments, user inputand user activity may not be used or available. According to variousembodiments, social, cultural, and genetic factors are analyzed at 307.Social, cultural, and genetic factors can have significant correlationswith visual element processing capabilities. In particular embodiments,younger subjects tend to be able to process approximately four or fivesimultaneous visual elements. The visual elements may be differentportions of a web page or different aspects of an image. In particularembodiments, older subjects tend to be able to processing approximatelythree or four simultaneous visual elements and may be more easilydistracted.

According to various embodiments, subjects are exposed to stimulushaving varying numbers of simultaneous visual elements at 309.Neuro-response data such as EEG, fMRI, MEG, and Electrooculography (EOG)data is received at 311. Neuro-response data may be measured andanalyzed on an individual basis, or on a subgroup and group basis.

FIG. 4 illustrates one example of response data associated with exposinga subject to simultaneous visual elements. Neuro-response significance401 is mapped as a function of time 403. According to variousembodiments, response 407 corresponds to an EEG response for a subjectexposed to one visual element. Response 409 may correspond to an EEGresponse for a subject exposed to two visual elements. Response 411 maycorrespond to an EEG response for a subject exposed to three visualelements.

According to various embodiments, a younger subject may exhibit EEGresponses corresponding to responses 415 and 417 when exposed to four orfive simultaneous visual elements respectively. However, other subjectsmay exhibit EEG responses corresponding to response 411 when exposed tothree, four, or five simultaneous visual elements. No additional neuralactivity may be measured as elements are added to an image. According tovarious embodiments, an older subject may show response 411 for a numberof simultaneous visual elements greater than or equal to three. Inparticular embodiments, a younger subject may show response 417 for anumber of simultaneous visual elements greater than or equal to five.

FIG. 5 illustrates one example of a system for evaluating neurologicalprofiles. Neuro-response data can be collected and analyzed to determineneurological profile characteristics such as introversion/extroversion,simultaneous visual elements processing capability, attention span, etc.Neuro-response data can also be used to select media appropriate to theneurological profile characteristics of a viewer for presentation to theviewer.

According to various embodiments, a system for evaluating neurologicalprofiles includes a stimulus presentation device 501. In particularembodiments, the stimulus presentation device 501 is merely a display,monitor, screen, speaker, etc., that provides stimulus material to auser. Continuous and discrete modes are supported. According to variousembodiments, the stimulus presentation device 501 also has protocolgeneration capability to allow intelligent customization of stimuliprovided to multiple subjects in different markets.

According to various embodiments, stimulus presentation device 501 couldinclude devices such as televisions, cable consoles, computers andmonitors, projection systems, display devices, speakers, tactilesurfaces, etc., for presenting the video and audio from differentnetworks, local networks, cable channels, syndicated sources, websites,internet content aggregators, portals, service providers, etc.

According to various embodiments, the subjects 503 are connected to datacollection devices 505. The data collection devices 505 may include avariety of neuro-response measurement mechanisms including neurologicaland neurophysiological measurements systems. According to variousembodiments, neuro-response data includes central nervous system,autonomic nervous system, and effector data.

Some examples of central nervous system measurement mechanisms includeFunctional Magnetic Resonance Imaging (fMRI), Magnetoencephalography(MEG), optical imaging, and Electroencephalography (EEG). fMRI measuresblood oxygenation in the brain that correlates with increased neuralactivity. However, current implementations of fMRI have poor temporalresolution of few seconds. MEG measures the magnetic fields produced byelectrical activity in the brain via extremely sensitive devices such assuperconducting quantum interference devices (SQUIDs). optical imagingmeasures deflection of light from a laser or infrared source todetermine anatomic or chemical properties of a material. EEG measureselectrical activity associated with post synaptic currents occurring inthe milliseconds range. Subcranial EEG can measure electrical activitywith the most accuracy, as the bone and dermal layers weakentransmission of a wide range of frequencies. Nonetheless, surface EEGprovides a wealth of electrophysiological information if analyzedproperly.

Autonomic nervous system measurement mechanisms include Galvanic SkinResponse (GSR), Electrocardiograms (EKG), pupillary dilation, etc.Effector measurement mechanisms include Electrooculography (EOG), eyetracking, facial emotion encoding, reaction time etc.

According to various embodiments, the techniques and mechanisms of thepresent invention intelligently blend multiple modes and manifestationsof precognitive neural signatures with cognitive neural signatures andpost cognitive neurophysiological manifestations to more accuratelyallow assessment of alternate media. In some examples, autonomic nervoussystem measures are themselves used to validate central nervous systemmeasures. Effector and behavior responses are blended and combined withother measures. According to various embodiments, central nervoussystem, autonomic nervous system, and effector system measurements areaggregated into a measurement that allows definitive evaluation stimulusmaterial

In particular embodiments, the data collection devices 505 include EEG511, EOG 513, and fMRI 515. In some instances, only a single datacollection device is used. Data collection may proceed with or withouthuman supervision.

The data collection device 505 collects neuro-response data frommultiple sources. This includes a combination of devices such as centralnervous system sources (EEG, MEG, fMRI, optical imaging), autonomicnervous system sources (EKG, pupillary dilation), and effector sources(EOG, eye tracking, facial emotion encoding, reaction time). Inparticular embodiments, data collected is digitally sampled and storedfor later analysis. In particular embodiments, the data collected couldbe analyzed in real-time. According to particular embodiments, thedigital sampling rates are adaptively chosen based on theneurophysiological and neurological data being measured.

In one particular embodiment, the system includes EEG 511 measurementsmade using scalp level electrodes, EOG 513 measurements made usingshielded electrodes to track eye data, functional Magnetic ResonanceImaging (fMRI) 515 measurements made non-invasively to show haemodynamicresponse related to neural activity, using a differential measurementsystem, a facial muscular measurement through shielded electrodes placedat specific locations on the face, and a facial affect graphic and videoanalyzer adaptively derived for each individual.

In particular embodiments, the data collection devices are clocksynchronized with a stimulus presentation device 501. In particularembodiments, the data collection devices 505 also include a conditionevaluation subsystem that provides auto triggers, alerts and statusmonitoring and visualization components that continuously monitor thestatus of the subject, data being collected, and the data collectioninstruments. The condition evaluation subsystem may also present visualalerts and automatically trigger remedial actions. According to variousembodiments, the data collection devices include mechanisms for not onlymonitoring subject neuro-response to stimulus materials, but alsoinclude mechanisms for identifying and monitoring the stimulusmaterials. For example, data collection devices 505 may be synchronizedwith a set-top box to monitor channel changes. In other examples, datacollection devices 505 may be directionally synchronized to monitor whena subject is no longer paying attention to stimulus material. In stillother examples, the data collection devices 505 may receive and storestimulus material generally being viewed by the subject, whether thestimulus is a program, a commercial, printed material, or a sceneoutside a window. The data collected allows analysis of neuro-responseinformation and correlation of the information to actual stimulusmaterial and not mere subject distractions.

According to various embodiments, the system also includes a datacleanser and analyzer device 521. In particular embodiments, the datacleanser and analyzer device 521 filters the collected data to removenoise, artifacts, and other irrelevant data using fixed and adaptivefiltering, weighted averaging, advanced component extraction (like PCA,ICA), vector and component separation methods, etc. This device cleansesthe data by removing both exogenous noise (where the source is outsidethe physiology of the subject, e.g. a phone ringing while a subject isviewing a video) and endogenous artifacts (where the source could beneurophysiological, e.g. muscle movements, eye blinks, etc.).

The artifact removal subsystem includes mechanisms to selectivelyisolate and review the response data and identify epochs with timedomain and/or frequency domain attributes that correspond to artifactssuch as line frequency, eye blinks, and muscle movements. The artifactremoval subsystem then cleanses the artifacts by either omitting theseepochs, or by replacing these epoch data with an estimate based on theother clean data (for example, an EEG nearest neighbor weightedaveraging approach).

According to various embodiments, the data cleanser and analyzer device521 is implemented using hardware, firmware, and/or software.

The data analyzer portion uses a variety of mechanisms to analyzeunderlying data in the system to determine resonance. According tovarious embodiments, the data analyzer customizes and extracts theindependent neurological and neuro-physiological parameters for eachindividual in each modality, and blends the estimates within a modalityas well as across modalities to elicit an enhanced response to thepresented stimulus material. In particular embodiments, the dataanalyzer aggregates the response measures across subjects in a dataset.

According to various embodiments, neurological and neuro-physiologicalsignatures are measured using time domain analyses and frequency domainanalyses. Such analyses use parameters that are common acrossindividuals as well as parameters that are unique to each individual.The analyses could also include statistical parameter extraction andfuzzy logic based attribute estimation from both the time and frequencycomponents of the synthesized response.

In some examples, statistical parameters used in a blended effectivenessestimate include evaluations of skew, peaks, first and second moments,distribution, as well as fuzzy estimates of attention, emotionalengagement and memory retention responses.

According to various embodiments, the data analyzer may include anintra-modality response synthesizer and a cross-modality responsesynthesizer. In particular embodiments, the intra-modality responsesynthesizer is configured to customize and extract the independentneurological and neurophysiological parameters for each individual ineach modality and blend the estimates within a modality analytically toelicit an enhanced response to the presented stimuli. In particularembodiments, the intra-modality response synthesizer also aggregatesdata from different subjects in a dataset.

According to various embodiments, the cross-modality responsesynthesizer or fusion device blends different intra-modality responses,including raw signals and signals output. The combination of signalsenhances the measures of effectiveness within a modality. Thecross-modality response fusion device can also aggregate data fromdifferent subjects in a dataset.

According to various embodiments, the data analyzer also includes acomposite enhanced effectiveness estimator (CEEE) that combines theenhanced responses and estimates from each modality to provide a blendedestimate of the effectiveness. In particular embodiments, blendedestimates are provided for each exposure of a subject to stimulusmaterials. The blended estimates are evaluated over time to assessresonance characteristics. According to various embodiments, numericalvalues are assigned to each blended estimate. The numerical values maycorrespond to the intensity of neuro-response measurements, thesignificance of peaks, the change between peaks, etc. Higher numericalvalues may correspond to higher significance in neuro-responseintensity. Lower numerical values may correspond to lower significanceor even insignificant neuro-response activity. In other examples,multiple values are assigned to each blended estimate. In still otherexamples, blended estimates of neuro-response significance aregraphically represented to show changes after repeated exposure.

According to various embodiments, a data analyzer passes data to aresonance estimator that assesses and extracts resonance patterns. Inparticular embodiments, the resonance estimator determines entitypositions in various stimulus segments and matches position informationwith eye tracking paths while correlating saccades with neuralassessments of attention, memory retention, and emotional engagement. Inparticular embodiments, the resonance estimator stores data in thepriming repository system. As with a variety of the components in thesystem, various repositories can be co-located with the rest of thesystem and the user, or could be implemented in remote locations.

FIG. 6 illustrates an example of a technique for analyzing neurologicalprofiles. At 601, a neurological profile for a user, user subgroup,and/or a user group is determined. According to various embodiments, theneurological profile may be determined using user input data, useractivity, social, genetic, and environmental factors, and neuro-responsedata. In particular embodiments, the neurological profile may also bederived based on demographic factors associated with the user. Accordingto various embodiments, templates corresponding to the neurologicalprofile are identified at 605. Templates may be identified by findingcorresponding EEG and fMRI response data. Templates may be associatedwith introverts, extroverts, detail oriented individuals, individualscapable of processing numerous simultaneous visual elements, etc.

According to various embodiments, the templates may be generated usingneuro-response data. For example, subjects known to be introvertsthrough a variety of measurements may have neuro-response measurementscollected and aggregated to create one or more introvert templates.

According to various embodiments, data analysis is performed. Dataanalysis may include intra-modality response synthesis andcross-modality response synthesis to enhance effectiveness measures. Itshould be noted that in some particular instances, one type of synthesismay be performed without performing other types of synthesis. Forexample, cross-modality response synthesis may be performed with orwithout intra-modality synthesis.

A variety of mechanisms can be used to perform data analysis. Inparticular embodiments, a stimulus attributes repository is accessed toobtain attributes and characteristics of the stimulus materials, alongwith purposes, intents, objectives, etc. In particular embodiments, EEGresponse data is synthesized to provide an enhanced assessment ofeffectiveness. According to various embodiments, EEG measures electricalactivity resulting from thousands of simultaneous neural processesassociated with different portions of the brain. EEG data can beclassified in various bands. According to various embodiments, brainwavefrequencies include delta, theta, alpha, beta, and gamma frequencyranges. Delta waves are classified as those less than 4 Hz and areprominent during deep sleep. Theta waves have frequencies between 3.5 to7.5 Hz and are associated with memories, attention, emotions, andsensations. Theta waves are typically prominent during states ofinternal focus.

Alpha frequencies reside between 7.5 and 13 Hz and typically peak around10 Hz. Alpha waves are prominent during states of relaxation. Beta waveshave a frequency range between 14 and 30 Hz. Beta waves are prominentduring states of motor control, long range synchronization between brainareas, analytical problem solving, judgment, and decision making. Gammawaves occur between 30 and 60 Hz and are involved in binding ofdifferent populations of neurons together into a network for the purposeof carrying out a certain cognitive or motor function, as well as inattention and memory. Because the skull and dermal layers attenuatewaves in this frequency range, brain waves above 75-80 Hz are difficultto detect and are often not used for stimuli response assessment.

However, the techniques and mechanisms of the present inventionrecognize that analyzing high gamma band (kappa-band: Above 60 Hz)measurements, in addition to theta, alpha, beta, and low gamma bandmeasurements, enhances neurological attention, emotional engagement andretention component estimates. In particular embodiments, EEGmeasurements including difficult to detect high gamma or kappa bandmeasurements are obtained, enhanced, and evaluated. Subject and taskspecific signature sub-bands in the theta, alpha, beta, gamma and kappabands are identified to provide enhanced response estimates. Accordingto various embodiments, high gamma waves (kappa-band) above 80 Hz(typically detectable with sub-cranial EEG and/ormagnetoencephalograophy) can be used in inverse model-based enhancementof the frequency responses to the stimuli.

Various embodiments of the present invention recognize that particularsub-bands within each frequency range have particular prominence duringcertain activities. A subset of the frequencies in a particular band isreferred to herein as a sub-band. For example, a sub-band may includethe 40-45 Hz range within the gamma band. In particular embodiments,multiple sub-bands within the different bands are selected whileremaining frequencies are band pass filtered. In particular embodiments,multiple sub-band responses may be enhanced, while the remainingfrequency responses may be attenuated.

An information theory based band-weighting model is used for adaptiveextraction of selective dataset specific, subject specific, taskspecific bands to enhance the effectiveness measure. Adaptive extractionmay be performed using fuzzy scaling. Stimuli can be presented andenhanced measurements determined multiple times to determine thevariation profiles across multiple presentations. Determining variousprofiles provides an enhanced assessment of the primary responses aswell as the longevity (wear-out) of the marketing and entertainmentstimuli. The synchronous response of multiple individuals to stimulipresented in concert is measured to determine an enhanced across subjectsynchrony measure of effectiveness. According to various embodiments,the synchronous response may be determined for multiple subjectsresiding in separate locations or for multiple subjects residing in thesame location.

Although a variety of synthesis mechanisms are described, it should berecognized that any number of mechanisms can be applied—in sequence orin parallel with or without interaction between the mechanisms.

Although intra-modality synthesis mechanisms provide enhancedsignificance data, additional cross-modality synthesis mechanisms canalso be applied. A variety of mechanisms such as EEG, Eye Tracking,fMRI, EOG, and facial emotion encoding are connected to a cross-modalitysynthesis mechanism. Other mechanisms as well as variations andenhancements on existing mechanisms may also be included. According tovarious embodiments, data from a specific modality can be enhanced usingdata from one or more other modalities. In particular embodiments, EEGtypically makes frequency measurements in different bands like alpha,beta and gamma to provide estimates of significance. However, thetechniques of the present invention recognize that significance measurescan be enhanced further using information from other modalities.

For example, facial emotion encoding measures can be used to enhance thevalence of the EEG emotional engagement measure. EOG and eye trackingsaccadic measures of object entities can be used to enhance the EEGestimates of significance including but not limited to attention,emotional engagement, and memory retention. According to variousembodiments, a cross-modality synthesis mechanism performs time andphase shifting of data to allow data from different modalities to align.In some examples, it is recognized that an EEG response will often occurhundreds of milliseconds before a facial emotion measurement changes.Correlations can be drawn and time and phase shifts made on anindividual as well as a group basis. In other examples, saccadic eyemovements may be determined as occurring before and after particular EEGresponses. According to various embodiments, fMRI measures are used toscale and enhance the EEG estimates of significance including attention,emotional engagement and memory retention measures.

Evidence of the occurrence or non-occurrence of specific time domaindifference event-related potential components (like the DERP) inspecific regions correlates with subject responsiveness to specificstimulus. According to various embodiments, ERP measures are enhancedusing EEG time-frequency measures (ERPSP) in response to thepresentation of the marketing and entertainment stimuli. Specificportions are extracted and isolated to identify ERP, DERP and ERPSPanalyses to perform. In particular embodiments, an EEG frequencyestimation of attention, emotion and memory retention (ERPSP) is used asa co-factor in enhancing the ERP, DERP and time-domain responseanalysis.

EOG measures saccades to determine the presence of attention to specificobjects of stimulus. Eye tracking measures the subject's gaze path,location and dwell on specific objects of stimulus. According to variousembodiments, EOG and eye tracking is enhanced by measuring the presenceof lambda waves (a neurophysiological index of saccade effectiveness) inthe ongoing EEG in the occipital and extra striate regions, triggered bythe slope of saccade-onset to estimate the significance of the EOG andeye tracking measures. In particular embodiments, specific EEGsignatures of activity such as slow potential shifts and measures ofcoherence in time-frequency responses at the Frontal Eye Field (FEF)regions that preceded saccade-onset are measured to enhance theeffectiveness of the saccadic activity data.

According to various embodiments, facial emotion encoding uses templatesgenerated by measuring facial muscle positions and movements ofindividuals expressing various emotions prior to the testing session.These individual specific facial emotion encoding templates are matchedwith the individual responses to identify subject emotional response. Inparticular embodiments, these facial emotion encoding measurements areenhanced by evaluating inter-hemispherical asymmetries in EEG responsesin specific frequency bands and measuring frequency band interactions.The techniques of the present invention recognize that not only areparticular frequency bands significant in EEG responses, but particularfrequency bands used for communication between particular areas of thebrain are significant. Consequently, these EEG responses enhance theEMG, graphic and video based facial emotion identification.

According to various embodiments, post-stimulus versus pre-stimulusdifferential measurements of ERP time domain components in multipleregions of the brain (DERP) are measured. The differential measures givea mechanism for eliciting responses attributable to the stimulus. Forexample the messaging response attributable to an advertisement or thebrand response attributable to multiple brands is determined usingpre-resonance and post-resonance estimates

Market categories associated with the templates are selected for theuser at 607. In particular embodiments, stimulus material associatedwith templates is selected at 609. For example, advertisements showinglarge gatherings of people may be selected for individuals having highextroversion levels. Advertisements having a large number ofsimultaneous visual elements may be selected for individuals having thecapability to process a larger number of simultaneous visual elements.At 611, stimulus material targeted to the neurological profile of theuser is presented to the user.

According to various embodiments, various mechanisms such as the datacollection mechanisms, the intra-modality synthesis mechanisms,cross-modality synthesis mechanisms, etc. are implemented on multipledevices. However, it is also possible that the various mechanisms beimplemented in hardware, firmware, and/or software in a single system.

FIG. 7 provides one example of a system that can be used to implementone or more mechanisms. For example, the system shown in FIG. 7 may beused to implement an alternate media system.

According to particular example embodiments, a system 700 suitable forimplementing particular embodiments of the present invention includes aprocessor 701, a memory 703, an interface 711, and a bus 715 (e.g., aPCI bus). When acting under the control of appropriate software orfirmware, the processor 701 is responsible for such tasks such aspattern generation. Various specially configured devices can also beused in place of a processor 701 or in addition to processor 701. Thecomplete implementation can also be done in custom hardware. Theinterface 711 is typically configured to send and receive data packetsor data segments over a network. Particular examples of interfaces thedevice supports include host bus adapter (HBA) interfaces, Ethernetinterfaces, frame relay interfaces, cable interfaces, DSL interfaces,token ring interfaces, and the like.

According to particular example embodiments, the system 700 uses memory703 to store data, algorithms and program instructions. The programinstructions may control the operation of an operating system and/or oneor more applications, for example. The memory or memories may also beconfigured to store received data and process received data.

Because such information and program instructions may be employed toimplement the systems/methods described herein, the present inventionrelates to tangible, machine readable media that include programinstructions, state information, etc. for performing various operationsdescribed herein. Examples of machine-readable media include, but arenot limited to, magnetic media such as hard disks, floppy disks, andmagnetic tape; optical media such as CD-ROM disks and DVDs;magneto-optical media such as optical disks; and hardware devices thatare specially configured to store and perform program instructions, suchas read-only memory devices (ROM) and random access memory (RAM).Examples of program instructions include both machine code, such asproduced by a compiler, and files containing higher level code that maybe executed by the computer using an interpreter.

Although the foregoing invention has been described in some detail forpurposes of clarity of understanding, it will be apparent that certainchanges and modifications may be practiced within the scope of theappended claims. Therefore, the present embodiments are to be consideredas illustrative and not restrictive and the invention is not to belimited to the details given herein, but may be modified within thescope and equivalents of the appended claims.

What is claimed is:
 1. A system for creating media based on a visualprocessing capability of a user, the system comprising: a sensor toobtain first neuro-response data from the user during exposure of theuser to first media and to obtain second neuro-response data duringexposure of the user to second media, the first media including a firstnumber of simultaneous visual elements and the second media including asecond number of simultaneous visual elements, the first numberdifferent than the second number; memory including instructions; and aprocessor to execute the instructions to: determine a maximum number ofsimultaneously presented visual elements in a stimulus that invokes anincrease in a user response in the user based on the firstneuro-response data and the second neuro-response data; assign asimultaneous visual element processing capability to the user based onthe maximum number of simultaneously presented visual elements; tailorsource media to have the maximum number of simultaneously presentedvisual elements corresponding to the simultaneous visual elementprocessing capability of the user to generate first tailored media; andoutput the first tailored media for exposure to the user.
 2. The systemof claim 1, wherein the processor is to: determine a first attentionlevel of the user based on the first neuro-response data; determine asecond attention level of the user based on the second neuro-responsedata; and determine the maximum number of simultaneously presentedvisual elements based on the first attention level and the secondattention level.
 3. The system of claim 1, wherein the processor is to:identify first neural activity in the first neuro-response data; detectan absence of the first neural activity in the second neuro-responsedata; and determine the maximum number of simultaneously presentedvisual elements based on the absence of the first neural activity in thesecond neuro-response data.
 4. The system of claim 3, wherein the sensorincludes an electrode and the first neuro-response data includeselectroencephalographic data, the processor to identify the first neuralactivity based on an interaction of a first frequency band of theelectroencephalographic data and a second frequency band of theelectroencephalographic data.
 5. The system of claim 1, wherein theprocessor is to generate a neurological profile for the user includingthe simultaneous visual element processing capability for the user. 6.The system of claim 5, wherein the processor is to: determine a detailprocessing level for the user based on the neurological profile; andtailor the source media based on the detail processing level to generatethe first tailored media.
 7. The system of claim 5, wherein theneurological profile is to further include one or more of demographicdata or age data for the user, the processor to tailor the source mediabased on the one or more of the demographic data or the age data togenerate the first tailored media.
 8. The system of claim 1, wherein theprocessor is to: access user purchase activity data; and tailor thesource media based on the user purchase activity data to generate thefirst tailored, media.
 9. The system of claim 1, wherein the user is afirst user, the user response is a first user response, the maximumnumber of simultaneously presented visual elements is a first maximumnumber of simultaneously presented visual elements, and the simultaneousvisual element processing capability is a first simultaneous visualelement processing capability, and the processor is to: determine asecond maximum number of simultaneously presented visual elements in thestimulus that invokes an increase in a second user response in a seconduser, the second maximum number of simultaneously presented visualelements different than the first maximum number of simultaneouslypresented visual elements; assign a second simultaneous visual elementprocessing capability to the second user based on the second maximumnumber of simultaneously presented visual elements, the secondsimultaneous visual element processing capability different than thefirst simultaneous visual element processing capability; and tailor thesource media to have the second maximum number of simultaneouslypresented visual elements corresponding to the second simultaneousvisual element processing capability of the second user to generatesecond tailored media, the second tailored media different than thefirst tailored media.
 10. The system of claim 9, wherein the processoris to: determine a detail processing level for the second user; andtailor the source media based on the detail processing level for thesecond user to generate the second tailored media.
 11. A tangiblemachine readable storage disk or storage device comprising instructionsthat, when executed, cause at least one machine to at least: determine amaximum number of simultaneously presented visual elements in a stimulusthat invokes an increase in a user response in a user based on firstneuro-response data obtained from the user during exposure of the userto first media including a first number of simultaneous visual elementsand second neuro-response data obtained from the user during exposure ofthe user to a second media including a second number of simultaneousvisual elements, the first number different from the second number;assign a simultaneous visual element processing capability to the userbased on the maximum number of simultaneously presented visual elements;tailor source media to have the maximum number of simultaneouslypresented visual elements corresponding to the simultaneous visualelement processing capability of the user to generate first tailoredmedia; and output the first tailored media for exposure to the user. 12.The storage device or storage disk of claim 11, wherein instructions,when executed, cause the at least one machine to: determine a firstattention level of the user based on the first neuro-response data;determine a second attention level of the user based on the secondneuro-response data; and determine the maximum number of simultaneouslypresented visual elements based on the first attention level and thesecond attention level.
 13. The storage device or storage disk of claim11, wherein instructions, when executed, cause the at least one machineto: identify first neural activity in the first neuro-response data;detect an absence of the first neural activity in the secondneuro-response data; and determine the maximum number of simultaneouslypresented visual elements based on the absence of the first neuralactivity in the second neuro-response data.
 14. The storage device orstorage disk of claim 13, wherein the first neuro-response data includeselectroencephalographic data and the instructions, when executed, causethe at least one machine to identify the first neural activity based onan interaction of a first frequency band of the electroencephalographicdata and a second frequency band of the electroencephalographic data.15. The storage device or storage disk of claim 11, wherein theinstructions, when executed, cause the at least one machine to generatea neurological profile for the user including the simultaneous visualelement processing capability for the user.
 16. The storage device orstorage disk of claim 15, wherein the instructions, when executed, causethe at least one machine: determine a detail processing level for theuser based on the neurological profile; and tailor the source mediabased on the detail processing level to generate the first tailoredmedia.
 17. The storage device or storage disk of claim 15, wherein theneurological profile is to further include one or more of demographicdata or age data for the user, and wherein instructions, when executed,cause the at least one machine to tailor the source media based on theone or more of the demographic data or the age data to generate thefirst tailored media.
 18. The storage device or storage disk of claim11, wherein instructions, when executed, cause the at least one machineto: access user purchase activity data; and tailor the source mediabased on the user purchase activity data generate the first tailoredmedia.
 19. The storage device or storage disk of claim 11, wherein theuser is a first user, the user response is a first user response, themaximum number of simultaneously presented visual elements is a firstmaximum number of simultaneously presented visual elements, and thesimultaneous visual element processing capability is a firstsimultaneous visual element processing capability, and instructions,when executed, cause the at least one machine to: determine a secondmaximum number of simultaneously presented visual elements in thestimulus to invoke an increase in a second user response in a seconduser, the second maximum number of simultaneously presented visualelements different than the first maximum number of simultaneouslypresented visual elements; assign a second simultaneous visual elementprocessing capability to the second user based on the second maximumnumber of simultaneously presented visual elements, the secondsimultaneous visual element processing capability different than thefirst simultaneous visual element processing capability; and tailor thesource media to have the second maximum number of simultaneouslypresented visual elements corresponding to the second simultaneousvisual element processing capability of the second user to generatesecond tailored media, the second tailored media different than thefirst tailored media.
 20. The storage device or storage disk of claim19, wherein instructions, when executed, cause the at least one machineto: determine a detail processing level for the second user; and tailorthe source media based on the detail processing level for the seconduser to generate the second tailored media.